Abstract
Chinese Legal documents contain complex underlying facts, controversies and legal application issues that make most domestic legal document retrieval platforms perform poorly in terms of relevance and accuracy. In this paper, we try to evaluate the performance of BERT on Chinese legal document classification. The data set for this paper is obtained from the legal judgment documents of a single charge on China Judicial Documents Network, with a total of 8 accusations and 2454 legal cases. The experimental result shows that the BERT performs much better than FastText, TextCNN, and RNN on our data set, obtaining a classification accuracy of 0.89.
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Acknowledgement
This research was funded by National Funds of Social Science (21BXW076), National Natural Science Foundation of China (61602518), Philosophy and Social Science Research Project of Hubei Provincial Department of Education (20G026), Innovation Research of Young Teachers of Central Universities in 2021 (2722021BZ040), The Key Social Science Projects in Wuhan in 2021 (2021010), Prof. Liu Yaqi’s Outstanding Youth Innovation team Construction Project (Big Data Intelligent Information Processing and Application Technology Innovation Team) and School-level reform project of Zhongnan University of Economics and Law (YB202158).
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Zhang, Q., Chen, X. (2023). Applying BERT on the Classification of Chinese Legal Documents. In: Barolli, L. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 161. Springer, Cham. https://doi.org/10.1007/978-3-031-26281-4_21
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DOI: https://doi.org/10.1007/978-3-031-26281-4_21
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